Impact on Care Process and Patient
Health Outcomes In 2001, Trow bridge and We in gartensummarized the results of several systematic reviews or meta-analyses of CDS RCTs. Since that paper, several new reviews and additional RCT studies have shown similar results.
The meta-analyses of studies of alerts and reminders for decision support have been fairly consistent in showing that they can alter clinician decision making and actions, reduce medication errors, and promote preventive screening and use of evidence-based recommendations for medication prescriptions. The data on how those decisions affect patient outcomes are more limited, although a number of studies have shown positive effects. Overall, the results indicate the potential of CDS to improve the quality of care.
Although the studies showing the ability of CDS to prevent medication errors (incorrect decisions) have been consistently positive, the results of research studies on the ability of CDS to avert adverse drug events (harm to the patient) have tended to be mixed. Few of the studies examining the impact on health outcomes were RCTs, many studies were poorly designed, and not all studies showed statistically significant effects.
In terms of other outcomes, in one recent randomized controlled trial of the impact of CDS on use of deep vein thrombosis (DVT) prophylaxis, mortality was improved with CDS however, well-designed studies of diabetes outcomes do not consistently show positive effects. CDS studies that focus on providing diagnostic decision support have also shown mixed results, and fewer of these systems have been evaluated in practice settings. However, studies comparing CDS diagnostic suggestions with expert clinicians’ analyses of challenging clinical cases have shown that the diagnostic CDS can remind even expert physicians of potentially important diagnoses they did not initially consider.
Some of the mixed results have resulted from methodological issues such as ceiling effects (performance was already very good prior to implementing CDS) or low statistical power to detect statistically significant effects for infrequently occurring events, such as adverse drug events. In addition, there are often intervening factors between the clinician decision that is influenced by CDS and the outcome for the patient. For instance, physicians may prescribe a medication suggested by the CDS, but patients may fail to take it. But even when looking at physician actions alone, many studies have shown that even when CDS recommendations are accurate and delivered in a timely manner, physicians have frequently ignored or overridden them.
This issue of ignoring the advice of the CDS has been shown for a variety of types of CDS including those that provide diagnostic suggestions, evidence-based treatment recommendations, or alerts for potentially dangerous drug interactions.
The problem of overriding drug interaction alerts, in particular, has been shown in inpatient, long-term care, and outpatient settings. Until there is a better understanding of why clinicians either do
not access, or choose to ignore, the CDS recommendations, assessing the effect of CDS on
quality will be very difficult. Because clinician decision making influences care processes, it is
important to examine the literature on why clinicians fail to utilize CDS suggestions.
Match of CDS to user intentions. In discussing the types of CDS, a distinction was made
between (1) systems that remind clinicians of things they intend to do, such as order sets that the
physician has customized to his or her preferences, and (2) systems that provide suggestions to
make clinicians reconsider what they intend to do. These latter suggestions may involve
additional diagnoses to consider, a change in medications from what the physician initially
prescribed, or reminders for tests that the physician did not initially intend to order. Most studies
of CDS have focused on the types that suggest that clinicians change their actions (e.g.,
medication alerts), rather than the types that remind clinicians of their intentions (e.g., order
sets). Studies of factors that make CDS effective have shown that it is more difficult to get users
to change their plans than to remind them of what they already intend to do. On-demand CDS systems appear less likely to be overridden than automatic alerts, but are viewed less frequently than those that are automatically displayed. The Institute of Medicine has emphasized that, to improve safety, health IT systems should be designed to make it “easy to do the right thing.” In a similar vein, Thaler and Sunstein in their book, Nudge,have focused on how “defaults” are set and advocated, making the default option (the option that does not require active choice on the part of the user) what is in the user’s best interest. This is particularly challenging in terms of CDS design. Because alerts are often presented automatically during the ordering process and usually indicate problems of varying severity, attempts to improve attention to them have focused on a variety of ways to present such alerts. The options include allowing the user to choose to view the information (on demand) rather than presenting it automatically; presenting alerts so they are not interruptive; or turning off or not requiring a response for the less serious alerts. When users seek out CDS information they are less likely to override it than when it is automatically presented to them; however, they choose to access the information very infrequently, reducing the overall impact. Attempts to make the alerts less interruptive by displaying the information (rather than calling attention to it or requiring an action) have found that such passive display does not attract the attention of the clinician and, in general, does not change behavior. User control, disruptiveness, and risk. Some have suggested turning off alerts that are frequently overridden, perhaps assuming that alerts that are ignored must be inaccurate or not needed. However, there is often lack of agreement about which alerts can be turned off without compromising safety. One approach that has been demonstrated to improve positive responses to alerts is what has been termed “tiered alerts.” In this approach the impacts of ignoring the alerts are rated for severity, with the display and users’ choices of action varying depending on the severity. For instance, alerts indicating a potentially life-threatening problem are presented automatically and may not allow overrides at all; those with less severe impact may be presented, but allow overrides with an explanation or rationale for the user’s decision and those alerts with the least severe consequences if ignored may be presented passively. Generally the alerts that are most frequently overridden—the majority of the alerts—are those that have a less severe impact when ignored. Most alerts fall into the less severe category because the current state of the art in CDS systems is such that the alerts are often very general, but in reality may be needed only by specific patient populations (e.g., elderly), by specific clinicians (e.g., less experienced), or in certain circumstances(e.g., first-time prescriptions).
Another effective approach has been to design standing orders for the nurse as part of the discharge process for interventions that are not time-sensitive, rather than alerting the physician while he or she is focused on more immediate orders. These examples illustrate three of the five rights: recipient, timing, and format. Integration of CDS into work processes. Research has shown that CDS that fits into the workflow is more likely to be used. However, integrating CDS into the workflow often requires unique customization to local processes, and sometimes to changes in processes (when previous clinical processes were found to be inefficient or ineffective). CDS also needs to be minimally
disruptive to the clinician’s “cognitive workflow” and this, too, can be a challenge. For instance, accessing the data needed for the CDS can be disruptive if the clinical systems are not well integrated or if the necessary data are not in a form that the CDS can use. If the lack of data leads to inappropriate alerts, these alerts may be overridden. In addition, to the extent that using CDS or following its advice is disruptive to the clinician’s work or thought processes, the CDS is
likely to be ignored.
It is clearly a challenge to implement CDS effectively in a way that ensures that alerts are raised whenever needed but with out inducing “alert fatigue.” A number of studies have identified the problem of overriding alerts and reminders, but further research is needed on methods to increase the specificity of the alerts and the effects of more specific alerts on physician overrides and patient outcomes. In addition, continuing research is needed on the design and impact of other types of CDS that may be less disruptive than alerts, such as order sets, other documentation tools, and info buttons, which are CDS features that present context-sensitive information during the care process that the user can choose on demand. These have been viewed positively by physicians and have shown promise in changing physician decision
Impact on Care Process and Patient
Health Outcomes In 2001, Trow bridge and We in gartensummarized the results of several systematic reviews or meta-analyses of CDS RCTs. Since that paper, several new reviews and additional RCT studies have shown similar results.
The meta-analyses of studies of alerts and reminders for decision support have been fairly consistent in showing that they can alter clinician decision making and actions, reduce medication errors, and promote preventive screening and use of evidence-based recommendations for medication prescriptions. The data on how those decisions affect patient outcomes are more limited, although a number of studies have shown positive effects. Overall, the results indicate the potential of CDS to improve the quality of care.
Although the studies showing the ability of CDS to prevent medication errors (incorrect decisions) have been consistently positive, the results of research studies on the ability of CDS to avert adverse drug events (harm to the patient) have tended to be mixed. Few of the studies examining the impact on health outcomes were RCTs, many studies were poorly designed, and not all studies showed statistically significant effects.
In terms of other outcomes, in one recent randomized controlled trial of the impact of CDS on use of deep vein thrombosis (DVT) prophylaxis, mortality was improved with CDS however, well-designed studies of diabetes outcomes do not consistently show positive effects. CDS studies that focus on providing diagnostic decision support have also shown mixed results, and fewer of these systems have been evaluated in practice settings. However, studies comparing CDS diagnostic suggestions with expert clinicians’ analyses of challenging clinical cases have shown that the diagnostic CDS can remind even expert physicians of potentially important diagnoses they did not initially consider.
Some of the mixed results have resulted from methodological issues such as ceiling effects (performance was already very good prior to implementing CDS) or low statistical power to detect statistically significant effects for infrequently occurring events, such as adverse drug events. In addition, there are often intervening factors between the clinician decision that is influenced by CDS and the outcome for the patient. For instance, physicians may prescribe a medication suggested by the CDS, but patients may fail to take it. But even when looking at physician actions alone, many studies have shown that even when CDS recommendations are accurate and delivered in a timely manner, physicians have frequently ignored or overridden them.
This issue of ignoring the advice of the CDS has been shown for a variety of types of CDS including those that provide diagnostic suggestions, evidence-based treatment recommendations, or alerts for potentially dangerous drug interactions.
The problem of overriding drug interaction alerts, in particular, has been shown in inpatient, long-term care, and outpatient settings. Until there is a better understanding of why clinicians either do
not access, or choose to ignore, the CDS recommendations, assessing the effect of CDS on
quality will be very difficult. Because clinician decision making influences care processes, it is
important to examine the literature on why clinicians fail to utilize CDS suggestions.
Match of CDS to user intentions. In discussing the types of CDS, a distinction was made
between (1) systems that remind clinicians of things they intend to do, such as order sets that the
physician has customized to his or her preferences, and (2) systems that provide suggestions to
make clinicians reconsider what they intend to do. These latter suggestions may involve
additional diagnoses to consider, a change in medications from what the physician initially
prescribed, or reminders for tests that the physician did not initially intend to order. Most studies
of CDS have focused on the types that suggest that clinicians change their actions (e.g.,
medication alerts), rather than the types that remind clinicians of their intentions (e.g., order
sets). Studies of factors that make CDS effective have shown that it is more difficult to get users
to change their plans than to remind them of what they already intend to do. On-demand CDS systems appear less likely to be overridden than automatic alerts, but are viewed less frequently than those that are automatically displayed. The Institute of Medicine has emphasized that, to improve safety, health IT systems should be designed to make it “easy to do the right thing.” In a similar vein, Thaler and Sunstein in their book, Nudge,have focused on how “defaults” are set and advocated, making the default option (the option that does not require active choice on the part of the user) what is in the user’s best interest. This is particularly challenging in terms of CDS design. Because alerts are often presented automatically during the ordering process and usually indicate problems of varying severity, attempts to improve attention to them have focused on a variety of ways to present such alerts. The options include allowing the user to choose to view the information (on demand) rather than presenting it automatically; presenting alerts so they are not interruptive; or turning off or not requiring a response for the less serious alerts. When users seek out CDS information they are less likely to override it than when it is automatically presented to them; however, they choose to access the information very infrequently, reducing the overall impact. Attempts to make the alerts less interruptive by displaying the information (rather than calling attention to it or requiring an action) have found that such passive display does not attract the attention of the clinician and, in general, does not change behavior. User control, disruptiveness, and risk. Some have suggested turning off alerts that are frequently overridden, perhaps assuming that alerts that are ignored must be inaccurate or not needed. However, there is often lack of agreement about which alerts can be turned off without compromising safety. One approach that has been demonstrated to improve positive responses to alerts is what has been termed “tiered alerts.” In this approach the impacts of ignoring the alerts are rated for severity, with the display and users’ choices of action varying depending on the severity. For instance, alerts indicating a potentially life-threatening problem are presented automatically and may not allow overrides at all; those with less severe impact may be presented, but allow overrides with an explanation or rationale for the user’s decision and those alerts with the least severe consequences if ignored may be presented passively. Generally the alerts that are most frequently overridden—the majority of the alerts—are those that have a less severe impact when ignored. Most alerts fall into the less severe category because the current state of the art in CDS systems is such that the alerts are often very general, but in reality may be needed only by specific patient populations (e.g., elderly), by specific clinicians (e.g., less experienced), or in certain circumstances(e.g., first-time prescriptions).
Another effective approach has been to design standing orders for the nurse as part of the discharge process for interventions that are not time-sensitive, rather than alerting the physician while he or she is focused on more immediate orders. These examples illustrate three of the five rights: recipient, timing, and format. Integration of CDS into work processes. Research has shown that CDS that fits into the workflow is more likely to be used. However, integrating CDS into the workflow often requires unique customization to local processes, and sometimes to changes in processes (when previous clinical processes were found to be inefficient or ineffective). CDS also needs to be minimally
disruptive to the clinician’s “cognitive workflow” and this, too, can be a challenge. For instance, accessing the data needed for the CDS can be disruptive if the clinical systems are not well integrated or if the necessary data are not in a form that the CDS can use. If the lack of data leads to inappropriate alerts, these alerts may be overridden. In addition, to the extent that using CDS or following its advice is disruptive to the clinician’s work or thought processes, the CDS is
likely to be ignored.
It is clearly a challenge to implement CDS effectively in a way that ensures that alerts are raised whenever needed but with out inducing “alert fatigue.” A number of studies have identified the problem of overriding alerts and reminders, but further research is needed on methods to increase the specificity of the alerts and the effects of more specific alerts on physician overrides and patient outcomes. In addition, continuing research is needed on the design and impact of other types of CDS that may be less disruptive than alerts, such as order sets, other documentation tools, and info buttons, which are CDS features that present context-sensitive information during the care process that the user can choose on demand. These have been viewed positively by physicians and have shown promise in changing physician decision
การแปล กรุณารอสักครู่..
